examples | ||
meanas | ||
.gitignore | ||
LICENSE.md | ||
README.md | ||
setup.py |
meanas
meanas is a python package for electromagnetic simulations
This package is intended for building simulation inputs, analyzing simulation outputs, and running short simulations on unspecialized hardware. It is designed to provide tooling and a baseline for other, high-performance purpose- and hardware-specific solvers.
Contents
- Finite difference frequency domain (FDFD)
- Library of sparse matrices for representing the electromagnetic wave equation in 3D, as well as auxiliary matrices for conversion between fields
- Waveguide mode operators
- Waveguide mode eigensolver
- Stretched-coordinate PML boundaries (SCPML)
- Functional versions of most operators
- Anisotropic media (limited to diagonal elements eps_xx, eps_yy, eps_zz, mu_xx, ...)
- Arbitrary distributions of perfect electric and magnetic conductors (PEC / PMC)
- Finite difference time domain (FDTD)
- Basic Maxwell time-steps
- Poynting vector and energy calculation
- Convolutional PMLs
This package does not provide a fast matrix solver, though by default
meanas.fdfd.solvers.generic(...)
will call
scipy.sparse.linalg.qmr(...)
to perform a solve.
For 2D FDFD problems this should be fine; likewise, the waveguide mode
solver uses scipy's eigenvalue solver, with reasonable results.
For solving large (or 3D) FDFD problems, I recommend a GPU-based iterative solver, such as opencl_fdfd or those included in MAGMA). Your solver will need the ability to solve complex symmetric (non-Hermitian) linear systems, ideally with double precision.
Installation
Requirements:
- python 3 (tests require 3.7)
- numpy
- scipy
Install with pip, via git:
pip install git+https://mpxd.net/code/jan/meanas.git@release
Use
See examples/
for some simple examples; you may need additional
packages such as gridlock
to run the examples.